Recent Advances in Tensor Based Signal and Image Processing
The goal of this special issue is to gather contributions that bring advances on tensor decompositions with applications to signal and image processing. Articles are invited which focus on either fundamental aspects of tensor decompositions or on application-oriented problems, or both. Fundamental issues include uniqueness, degeneracy, rank definitions and determination, low-rank approximation, structured tensors, constrained tensor models/decompositions, and algorithms. Application fields include (but are not limited to): modeling/ estimation of wireless communication channels, blind equalization and source separation, transceiver design for MIMO and cooperative communication systems, modeling and identification of non-linear systems, biomedical and genomic signal processing, image processing, and audio/ speech processing.
Edited by: Andre Almeida, Gérard Favier, Martin Haardt, Morten Mørup and Alex Vasilescu